Phosphorus Management

Soils with high levels of P can contribute to excess P in runoff and subsequently pollute the surface water. Excess P in the soil can be removed from the system by harvesting crops. The objectives of this study were to evaluate corn (Zea mays L.) P removal effects on soil P reduction, and to evaluate various corn hybrids and soybean [Glycine max (L.) Merr.] varieties for differences in grain P concentration and P removal. Soil with varying P levels as a result of annual or biennial beef cattle (Bos Taurus) feedlot manure or compost application was cropped to corn for 4 yr without any P addition. In other studies under various water and N regimes, corn hybrids and soybean varieties were evaluated for grain P concentration and P removal. Four years of corn production without P addition lowered surface soil (0–15 cm) extractable P level (Bray and Kurtz no. 1) from 265 mg kg-1 to 171 mg kg-1 in the biennial N-based compost treatment. Based on a decay equation, it would have required 10 yr of corn P removal P to lower the soil P level to the original 69 mg kg-1 that existed before treatment application. The rate of decrease in extractable soil P was greater when soil P was higher and reduced with decreasing soil P level. Most of the P in the plants was absorbed from the 0- to 15-cm soil depth since no significant reduction in soil P level was observed from 1996 to 1999 in the 15- to 30-cm soil depth. Across 2 yr, there was as much as 54% difference among corn hybrids for grain P removal. The differences in P concentrations among corn hybrids indicated that hybrids could be selected for low P uptake when P level in ethanol production by-product or in animal ration and subsequently in manure is desired. Soybean grain P concentration was nearly twice that for corn but grain P removal was less for soybean than for corn. Crop P removal can significantly reduce soil P level with time

Phosphorus Management

Soils with high levels of P can contribute to excess P in runoff and subsequently pollute the surface water. Excess P in the soil can be removed from the system by harvesting crops. The objectives of this study were to evaluate corn (Zea mays L.) P removal effects on soil P reduction, and to evaluate various corn hybrids and soybean [Glycine max (L.) Merr.] varieties for differences in grain P concentration and P removal. Soil with varying P levels as a result of annual or biennial beef cattle (Bos Taurus) feedlot manure or compost application was cropped to corn for 4 yr without any P addition. In other studies under various water and N regimes, corn hybrids and soybean varieties were evaluated for grain P concentration and P removal. Four years of corn production without P addition lowered surface soil (0–15 cm) extractable P level (Bray and Kurtz no. 1) from 265 mg kg-1 to 171 mg kg-1 in the biennial N-based compost treatment. Based on a decay equation, it would have required 10 yr of corn P removal P to lower the soil P level to the original 69 mg kg-1 that existed before treatment application. The rate of decrease in extractable soil P was greater when soil P was higher and reduced with decreasing soil P level. Most of the P in the plants was absorbed from the 0- to 15-cm soil depth since no significant reduction in soil P level was observed from 1996 to 1999 in the 15- to 30-cm soil depth. Across 2 yr, there was as much as 54% difference among corn hybrids for grain P removal. The differences in P concentrations among corn hybrids indicated that hybrids could be selected for low P uptake when P level in ethanol production by-product or in animal ration and subsequently in manure is desired. Soybean grain P concentration was nearly twice that for corn but grain P removal was less for soybean than for corn. Crop P removal can significantly reduce soil P level with time

Appropriateness of Management Zones for Characterizing Spatial Variability of Soil Properties and Irrigated Corn Yields across Years

Recent precision-agriculture research has focused on use of management zones (MZ) as a method for variable application of inputs like N. The objectives of this study were to determine (i) if landscape attributes could be aggregated into MZthat characterize spatial varia- tion in soil chemical properties and corn yields and (ii) if temporal variability affects expression of yield spatial variability. This work was conducted on an irrigated cornfield near Gibbon, NE. Five landscape attributes, including a soil brightness image (red, green, and blue bands), elevation, and apparent electrical conductivity, were acquired for the field.Ageoreferenced soil-sampling scheme was used to determine soil chemical properties (soil pH, electrical conductivity, P, and organic matter). Georeferenced yield monitor data were collected for five (1997–2001) seasons. The five landscape attributes were aggregated into four MZ using principal-component analysis of landscape attributes and unsupervised classification of principal-component scores. All of the soil chemical properties differed among the four MZ. While yields were observed to differ by up to 25% between the highest- and lowest-yielding MZ in three of five seasons, receiving average precipitation, less-pronounced (≤5%) differences were noted among the same MZ in the driest and wettest seasons. This illustrates the significant role temporal variability plays in altering yield spatial variability, even under irrigation. Use of MZ for variable application tem, of inputs like N would only have been appropriate for this field in three out of the five seasons, seriously restricting the use of this approach under variable environmental conditions

Appropriateness of Management Zones for Characterizing Spatial Variability of Soil Properties and Irrigated Corn Yields across Years

Recent precision-agriculture research has focused on use of management zones (MZ) as a method for variable application of inputs like N. The objectives of this study were to determine (i) if landscape attributes could be aggregated into MZthat characterize spatial varia- tion in soil chemical properties and corn yields and (ii) if temporal variability affects expression of yield spatial variability. This work was conducted on an irrigated cornfield near Gibbon, NE. Five landscape attributes, including a soil brightness image (red, green, and blue bands), elevation, and apparent electrical conductivity, were acquired for the field.Ageoreferenced soil-sampling scheme was used to determine soil chemical properties (soil pH, electrical conductivity, P, and organic matter). Georeferenced yield monitor data were collected for five (1997–2001) seasons. The five landscape attributes were aggregated into four MZ using principal-component analysis of landscape attributes and unsupervised classification of principal-component scores. All of the soil chemical properties differed among the four MZ. While yields were observed to differ by up to 25% between the highest- and lowest-yielding MZ in three of five seasons, receiving average precipitation, less-pronounced (≤5%) differences were noted among the same MZ in the driest and wettest seasons. This illustrates the significant role temporal variability plays in altering yield spatial variability, even under irrigation. Use of MZ for variable application tem, of inputs like N would only have been appropriate for this field in three out of the five seasons, seriously restricting the use of this approach under variable environmental conditions

Use of Remote-Sensing Imagery to Estimate Corn Grain Yield

Remote sensing—the process of acquiring information about objects from remote platforms such as ground-based booms, aircraft, or satellites—is a potentially important source of data for site-specific crop management, providing both spatial and temporal information. Our objective was to use remotely sensed imagery to compare different vegetation indices as a means of assessing canopy variation and its resultant impact on corn (Zea mays L.) grain yield. Treatments consisted of five N rates and four hybrids, which were grown under irrigation near Shelton, NE on a Hord silt loam in 1997 and 1998. Imagery data with 0.5-m spatial resolution were collected from aircraft on several dates during both seasons using a multispectral, four-band [blue, green, red, and near-infrared reflectance] digital camera system. Imagery was imported into a geographical information system (GIS) and then geo-registered, converted into reflectance, and used to compute three vegetation indices. Grain yield for each plot was determined at maturity. Results showed that green normalized difference vegetation index (GNDVI) values derived from images acquired during midgrain filling were the most highly correlated with grain yield; maximum correlations were 0.7 and 0.92 in 1997 and 1998, respectively. Normalizing GNDVI and grain yield variability within hybrids improved the correlations in both years, but more dramatic increases were observed in 1997 (0.7 to 0.82) than in 1998 (0.92 to 0.95). This suggested GNDVI acquired during midgrain filling could be used to produce relative yield maps depicting spatial variability in fields, offering a potentially attractive alternative to use of a combine yield monitor

Using Heavy Quark Spin Symmetry in Semileptonic BcB_c Decays

The form factors parameterizing the B_c semileptonic matrix elements can be related to a few invariant functions if the decoupling of the spin of the heavy quarks in B_c and in the mesons produced in the semileptonic decays is exploited. We compute the form factors as overlap integral of the meson wave-functions obtained using a QCD relativistic potential model, and give predictions for semileptonic and non-leptonic B_c decay modes. We also discuss possible experimental tests of the heavy quark spin symmetry in B_c decays.Comment: RevTex, 22 pages, 2 figure

Responsive in-season nitrogen management for cereals

Current nitrogen (N) management strategies for worldwide cereal production systems are characterized by low N use efficiency (NUE), environmental contamination, and considerable ongoing debate regarding what can be done to improve N fertilizer management. Development of innovative strategies that improve NUE and minimize off-field losses is crucial to sustaining cereal-based farming. In this paper, we review the major managerial causes for low NUE, including (1) poor synchrony between fertilizer N and crop demand, (2) uniform field applications to spatially variable landscapes that commonly vary in crop N need, and (3) failure to account for temporally variable influences on crop N needs. Poor synchronization is mainly due to large pre-plant applications of fertilizer N, resulting in high levels of inorganic soil N long before rapid crop uptake occurs. Uniform applications within fields discount the fact that N supplies from the soil, crop N uptake, and crop response are spatially variable. Current N management decisions also overlook year-to-year weather variations and sometimes fail to account for soil N mineralized in warm, wet years, ignoring indigenous N supply. The key to optimizing tradeoffs amongst yield, profit, and environmental protection is to achieve synchrony between N supply and crop demand, while accounting for spatial and temporal variability in soil N. While some have advocated a soil-based management zones (MZ) approach as a means to direct variable N applications and improve NUE, this method disregards yearly variation in weather. Thus, it seems unlikely that the soil-based MZ concept alone will be adequate for variable application of crop N inputs. Alternatively, we propose utilizing emerging computer and electronic technologies that focus on the plant to assess N status and direct in-season spatially variable N applications. Several of these technologies are reviewed and discussed. One technology showing promise is ground-based active-light reflectance measurements converted to NDVI or other similar indices. Preliminary research shows this approach addresses the issue of spatial variability and is accomplished at a time within the growing season so that N inputs are synchronized to match crop N uptake. We suggest this approach may be improved by first delineating a field into MZ using soil or other field properties to modify the decision associated with ground-based reflectance sensing. While additional adaptive research is needed to refine these newer technologies and subsequent N management decisions, preliminary results are encouraging.We expect N use efficiency can be greatly enhanced using this plant-based responsive strategy for N management in cereals

Standard Model Matrix Elements for Neutral B-Meson Mixing and Associated Decay Constants

We present results of quenched lattice calculations of the matrix elements relevant for B_d-\bar B_d and B_s-\bar B_s mixing in the Standard Model. Results for the corresponding SU(3)-breaking ratios, which can be used to constrain or determine |V_{td}|, are also given. The calculations are performed at two values of the lattice spacing, corresponding to \beta = 6.0 and \beta = 6.2, with quarks described by a mean-field-improved Sheikholeslami-Wohlert action. As a by-product, we obtain the leptonic decay constants of B and D mesons. We also present matrix elements relevant for D^0-\bar D^0 mixing. Our results are summarized in the Introduction.Comment: 27 pages (RevTeX), 26 figures, version published in Phys. Rev. D: improved estimate of the systematic error associated with the uncertainty on the strange quark mass and other small improvements to analysis (results change only slightly); correction of typos and minor changes to text; RevTeX formattin